Top Machine Learning Jobs in Toronto

The Head of Machine Learning will manage 9 ML engineers, coordinate projects, contribute to system architecture, and promote team growth. Responsibilities include strategic leadership, project management, and technical mentorship to align ML initiatives with business goals.

The role involves developing cutting-edge AI/ML models for biology, leading research strategy, and mentoring. Requires expertise in machine learning methodologies and experience in biological data.

Partner with multinational clients to gather requirements, define KPIs, develop business cases, and oversee GRAVTY® loyalty program implementations. Provide product expertise, deliver client training, manage project documentation and SLAs, collaborate with product management on features, and create product marketing collaterals to support go-to-market strategies.

The AI Engineer role focuses on enhancing applied AI systems, developing tools for LLM applications, and optimizing workflows while collaborating with the product team.

The Machine Learning Intern will design and train models, develop AI agents, and work with teams to create impactful applications.

The Senior Software Engineer will design and build scalable data and ML platforms, ensuring high-quality data flow while improving system efficiency and supporting internal teams.

Build scalable ML data pipelines for Waabi's autonomous driving platform. Design, optimize, and manage datasets and training processes while collaborating with scientists and engineers.

The AI Transformation Lead will drive AI delivery capabilities, transforming internal operations and client programs, while embedding AI practices and managing teams to ensure successful implementation and measurable outcomes.

Lead the design and deployment of AI/ML solutions for grid automation, manage teams, drive innovation, and ensure adherence to architectural standards.

As a Senior Machine Learning Engineer, you will optimize LLM inference algorithms, collaborate with product and research teams, and develop robust deep learning systems.

You will lead full-stack development and manage engineering teams responsible for building scalable web platforms and search systems using ML techniques.

Develop end-to-end software agents as collaborative AI teammates to empower engineering teams in solving complex challenges.

The Head of Startup Program will create and manage an AI-centric startup program, drive customer engagement, and establish strategic partnerships in the ecosystem.

Design, develop, and deploy scalable machine learning solutions, integrate ML with data warehouses, and optimize model performance in production environments.

The Advisor will provide strategic capital guidance to AI/software companies, assist in transaction readiness, and support program delivery at MaRS.

As an Engineering Manager for Inference ML Runtime, you will lead a team to design, scale, and optimize AI inference systems on Cerebras hardware, ensuring high performance and overseeing execution of ML engineering initiatives.

Lead product strategy and execution at Findem, focusing on delivering insights and coordinating with cross-functional teams. Own the product development process and drive innovation while aligning with market needs.

As an AI/ML Product Manager at Versapay, you'll manage products that leverage machine learning solutions, drive change, and enhance customer experience across platforms from ideation to implementation.

Develop and deploy scalable deep learning and reinforcement learning systems, optimize performance, and collaborate with data teams at Quincus.

The ML Developer Experience Engineer will create tooling and workflows for ML developers, enhance customer adoption, and ensure high-quality developer experiences through collaboration and documentation.

The role involves developing algorithms for inference optimization, building compiler components, and collaborating across teams to enhance performance on NVIDIA platforms.

Develop AI technologies for clinical trials, focusing on scalable ML infrastructure, optimizing models, and working cross-functionally to enhance safety and efficiency.

As an Associate Technical Architect in Machine Learning, you will design and develop advanced ML models on AWS, ensuring scalability and reliability while collaborating with cross-functional teams.

The Data Intern will analyze content from pharma/biotech/MedTech sources, focusing on data quality and sourcing using machine learning methods. Tasks include spreadsheet manipulation and prompt engineering for LLMs, collaborating with data teams for industry insights.

The Staff Machine Learning Engineer will develop advanced Document AI models, solve complex modeling challenges, lead LLM fine-tuning, and provide leadership in a collaborative environment.